Web-based Supplementary Materials for "Bayesian nonparametric estimation of targeted agent effects on biomarker change to predict clinical outcome," by
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چکیده
Prostate Cancer Trial Data Testing Assumptions. We test the validity of the simplifying assumption of no association between the distributions of the PDGFR values X and Y and the other covariates Z in the PFS model, by regressing the individual preand posttreatment mean values on hemoglobin levels and increase in prostate antigen levels. No significant association was revealed by such analysis. Here, we report the results of the marginal regression of the mean values on each variable. Multivariable regressions confirmed the results of the marginal analyses.
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Bayesian nonparametric estimation of targeted agent effects on biomarker change to predict clinical outcome.
The effect of a targeted agent on a cancer patient's clinical outcome putatively is mediated through the agent's effect on one or more early biological events. This is motivated by pre-clinical experiments with cells or animals that identify such events, represented by binary or quantitative biomarkers. When evaluating targeted agents in humans, central questions are whether the distribution of...
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